Comparisons of sensitivity improvement techniques for linear optimal control systems.
Sensitivity function in time domain defined for control system design
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Sensitivity function in time domain defined for control system design
Two holographic data storage and display systems, voltage gradient ionization system, and linear strain manipulation system are discussed in terms of creating fast, high bit density, storage device. Components described include: novel mounting fixture for photoplastic arrays; corona discharge device; and block data composer.
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The instrument pointing system concept discussed in the present paper was developed for Spacelab missions. The system is mounted on soft shockmounts to minimize Shuttle disturbances (such as man motion, thruster firings, etc.) and to reduce the effect of large center of mass offsets between the instrument and the pointing system gimbal axes. The instrument pointing system is soft mounted to the Spacelab pallet located in the Orbiter payload bay. The nonlinear model, incorporating the dynamic equations of motion, the controller equations and the definition of sensor dynamics and gimbal bearing friction, is given, along with a system of linearized equations of motion of the Space Shuttle Orbiter and instrument pointing system (linearized model).
An interactive computer program (AESOP) which solves quadratic optimal control and is discussed. The program can also be used to perform system analysis calculations such as transient and frequency responses, controllability, observability, etc., in support of the control and filter design computations.
Systems described by partial differential equations have an infinite-dimensional state space. Feedback control of such distributed parameter systems must be accomplished by finite-dimensional controllers to be implemented by on-line digital computers. A further practical constraint is that the controller must operate in discrete (rather than continuous) time. This paper investigates the stability of such distributed parameter feedback controllers in closed-loop with the actual system.
Some unique properties on a class of the second order lambda matrices were found and applied to determine a damping matrix of the decoupled subsystem in such a way that the damped system would have preassigned eigenvalues without disturbing the stiffness matrix. The resulting system was realized as a time invariant velocity only feedback control system with desired poles. Another approach using optimal control theory was also applied to the decoupled system in such a way that the mode spillover problem could be eliminated. The procedures were tested successfully by numerical examples.
A finite-element method for the solution of nonlinear hyperbolic systems of equations, such as those encountered in non-self-adjoint problems of transient phenomena in convection-diffusion or in the mixed representation of wave problems, is developed and demonstrated. The problem is rewritten in moving coordinates and reinterpolated to the original mesh by a Taylor expansion prior to a standard Galerkin spatial discretization, and it is shown that this procedure is equivalent to the time-discretization approach of Donea (1984). Numerical results for sample problems are presented graphically, including such shallow-water problems as the breaking of a dam, the shoaling of a wave, and the outflow of a river; compressible flows such as the isothermal flow in a nozzle and the Riemann shock-tube problem; and the two-dimensional scalar-advection, nonlinear-shallow-water, and Euler equations.
In a typical design process major decisions are made sequentially. An illustrated example is given for an aircraft design in which the aerodynamic shape is usually decided first, then the airframe is sized for strength and so forth. An analogous sequence could be laid out for any other major industrial product, for instance, a ship. The loops in the discipline boxes symbolize iterative design improvements carried out within the confines of a single engineering discipline, or subsystem. The loops spanning several boxes depict multidisciplinary design improvement iterations. Omitted for graphical simplicity is parallelism of the disciplinary subtasks. The parallelism is important in order to develop a broad workfront necessary to shorten the design time. If all the intradisciplinary and interdisciplinary iterations were carried out to convergence, the process could yield a numerically optimal design. However, it usually stops short of that because of time and money limitations. This is especially true for the interdisciplinary iterations.
A simple method for determination and correction of nonlinaearity in measurement systems is presented. The technique is applicable to a wide range of measuring systems. The basic concept, an analysis, and a sample application are given. Nonlinearity of the Goldstone DSS 13 low noise HEMT 2.3 GHz (S-band) radiometer system results in noise temperature measurement errors. These errors are successfully correct with this method.
Design procedures are developed to select both eigenvalues and eigenvectors to improve system robustness. A robustness metric based on the determinant of the normalized eigenvector matrix defined. It is shown that this metric significantly speeds up the convergence of robust eigenvector solutions close to the optimal. A procedure to blend multiple inputs to improve achievable system robustness in the lower dimensional pseudo control space has also been derived.
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Methods to synthesize controllers for nonlinear systems are developed by exploiting the fact that under mild differentiability conditions, systems of the form: x-dot = f(x) + G(x)u can be represented in quasilinear form, viz: x-dot = A(x)x + B(x)u. Two classes of control methods are investigated. The first is zero-look-ahead control, where the control input depends only on the current values of A(x) and B(x). For this case the control input is computed by continuously solving a matrix Riccati equation as the system progresses along a trajectory. The second is controllers with look-ahead, where the control input depends on the future behavior of A(x) and B(x). These controllers use the similarity between quasilinear systems and linear time varying systems to find approximate solutions to optimal control type problems. The methods that are developed are not guaranteed to be globally stable. However in simulation studies they were found to be useful alternatives for synthesizing control laws for a general class of nonlinear systems.
Solid-state array imaging has become an indispensable tool for various modem scientific instrumentation and industrial applications. Often in experiments, use of an imaging system with linear response is very desirable. The linearity of commercial products, however, has yet to be accurately determined in order to assess their nonlinearity effects. Linearity is affected both by sensors and electronics. It is also very desirables to employ low-cost products if we can provide the performance comparable of expensive ones through calibration. Here, we present a very simple approach for approximately checking linearity of imaging systems and also a simple calibration method for precisely measuring intensity ratio or relative intensity variation. These methods can be readily implemented with existing equipment. The calibration method works well with an intermediate-grade analog sensor interfaced by a frame grabber. In our initial attempt for calibration, the nonlinearity of the camera can be reduced from about five percent to much less than one percent in standard deviation.
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